| #!/usr/bin/env bash | |
| set -euo pipefail | |
| # patch-claude-code.sh — Rebalance Claude Code prompts to fix corner-cutting behavior | |
| # | |
| # What this does: | |
| # Patches the npm-installed @anthropic-ai/claude-code cli.js to rebalance | |
| # system prompt instructions that cause the model to cut corners, simplify | |
| # excessively, and defer complicated work. | |
| # |
Following commands disables Microsoft AutoUpdate launch agent from launching at boot and periodicaly checking for updates.
sudo defaults write /Library/LaunchAgents/com.microsoft.update.agent.plist Disabled -bool YES
sudo defaults write /Library/LaunchAgents/com.microsoft.update.agent.plist RunAtLoad -bool NO
sudo chflags schg /Library/LaunchAgents/com.microsoft.update.agent.plist
A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.
The core of most real-time fluid simulators, like the one in EmberGen, are based on the "Stable Fluids" algorithm by Jos Stam, which to my knowledge was first presented at SIGGRAPH '99. This is a post about one part of this algorithm that's often underestimated: Projection
The Stable Fluids algorithm solves a subset of the famous "Navier Stokes equations", which describe how fluids interact and move. In particular, it typically solves what's called the "incompressible Euler equations", where viscous forces are often ignored.
A pattern for building personal knowledge bases using LLMs. Extended with lessons from building agentmemory 20K+ Stars ⭐️, a persistent memory engine for AI coding agents.
This builds on Andrej Karpathy's original LLM Wiki idea file. Everything in the original still applies. This document adds what we learned running the pattern in production: what breaks at scale, what's missing, and what separates a wiki that stays useful from one that rots.
The core insight is correct: stop re-deriving, start compiling. RAG retrieves and forgets. A wiki accumulates and compounds. The three-layer architecture (raw sources, wiki, schema) works. The operations (ingest, query, lint) cover the basics. If you haven't read the original, start there.
| /* Based on codemedic's work (https://gist.github.com/codemedic/f11cc460b8d9544f9afc) */ | |
| QWidget, QTabWidget::pane, QTabWidget::tab-bar { | |
| background-color: #383c4a; | |
| } | |
| QTabBar::tab { | |
| color: #777; | |
| background-color: #383c4a; /* Pick from current color scheme from System Settings > Color > Modify > Colors > Window Background */ | |
| font-size: 16px; | |
| height: 32px; | |
| padding: 8px; |
| /* | |
| Author: Arno0x0x, Twitter: @Arno0x0x | |
| Completely based on @Flangvik netloader | |
| This partial rewrite of @Flangvik Netloader includes the following changes: | |
| - Allow loading of an XOR encrypted binary to bypass antiviruses | |
| To encrypt the initial binary you can use my Python transformFile.py script. | |
| Example: ./transformFile.py -e xor -k mightyduck -i Rubeus.bin -o Rubeus.xor | |
Never ask the user to copy-paste code. Instead, use Slicer web server that allows execution of Python code via a web API.
Give these instructions to the user: Go to Web Server module, enable "Slicer API exec" in Advanced section, and click "Start server".
After this, you can connect to Slicer and run Python commands as it is described here: https://slicer.readthedocs.io/en/latest/user_guide/modules/webserver.html#remote-control